Waste recycling: share in the structure of the tariff for the treatment of solid municipal waste in the Vologda region
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the modern world, the issues of solid municipal waste disposal, as part of the problem of environmental protection, are quite acute These problems are relevant for Russia and for many other world powers. The Russian Federation is one of the most polluted countries in the world, which negatively affects the quality of life and the health of the population of its regions. The annual increase in the volume of municipal solid waste is part of the man-made impact of man on the natural environment. To make strategic decisions on this issue, it is necessary to understand the policy of MSW management, so the authors in the article consider the values of tariffs for MSW management in one of the major regions of Russia - the Vologda Region. The data of tariffs of the Vologda region approved for 2021 are given. The structure of the average tariffs of the Russian Federation and the Vologda Region is analyzed. On the basis of regional regulations, a sample of data on the costs of disposal and transportation of MSW for some districts of the Vologda region is given: Velikoustugski, Totemski, Mezhdurechensky, Babushkinsky area, Belozersky districts. The average values of tariffs for the treatment of MSW for Russia and other countries are given: the USA, Canada, Germany, France and Finland. In addition to tariffs, the authors conducted a study on the distribution of MSW by type of disposal: disposal, incineration and recycling The article discusses the values of tariffs for the treatment of solid municipal waste and their disposal. In conclusion, the authors express concern about insufficient funds for innovations in the field of MSW processing/ recycling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it